Discovering TikTok Shop Sellers by Niche

Maps the TikTok Shop seller landscape in a product category. Identifies which products are being heavily promoted, which creators drive the most sales content, and where product gaps exist.

Prerequisites

• APIFY_TOKEN environment variable set
• Optional: Apify MCP server installed

Inputs

Workflow

Progress:
- [ ] Step 1: Search niche hashtags with TikTok Shop signals
- [ ] Step 2: Filter posts with shop product links
- [ ] Step 3: Extract seller profiles and products
- [ ] Step 4: Rank by sales signal strength
- [ ] Step 5: Deliver seller/product map

Step 1: Search Hashtags

TikTok Shop hashtags: #tiktokshop[niche], #[niche]shop, #[niche]deals, #tiktokmademebuyit,
                      #[niche]affiliate, #[niche]haul

Recommended — run_actor.js (handles waiting, output, and file saving automatically):

# Quick answer (prints table to chat)
node scripts/run_actor.js \
  --actor "apidojo~tiktok-scraper" \
  --input '{"param": "value"}'

# Save as CSV
node scripts/run_actor.js \
  --actor "apidojo~tiktok-scraper" \
  --input '{"param": "value"}' \
  --output YYYY-MM-DD_results.csv --format csv

# Save as JSON
node scripts/run_actor.js \
  --actor "apidojo~tiktok-scraper" \
  --input '{"param": "value"}' \
  --output YYYY-MM-DD_results.json --format json

APIFY_TOKEN must be set in environment or .env file.

If Apify MCP is available:

Tool: apify:run-actor
Actor: "apidojo~tiktok-scraper"
Input:
{
  "keywords": ["#tiktokshop", "#[niche]shop", "#tiktokmademebuyit"],
  "maxItems": 300
}

REST API fallback:

curl -X POST   "https://api.apify.com/v2/acts/apidojo~tiktok-scraper/runs?token=$APIFY_TOKEN"   -H "Content-Type: application/json"   -d '{
    "keywords": ["#tiktokshop", "#kitchentools", "#tiktokmademebuyit"],
    "maxItems": 300
  }'

Step 2: Score Seller Strength

sales_signal = (playCount / 10000) * 0.35
             + (diggCount / 1000) * 0.25
             + (commentCount / 100) * 0.15
             + (shareCount / 500) * 0.15
             + (hasShopLink ? 1 : 0) * 0.10

Normalize to [0, 1]. Sellers with multiple high-signal posts get multi_post_bonus = 0.15.

Step 3: Classify Seller Type

seller_type:
  BRAND = account.verified OR followerCount > 50K AND bio contains brand name
  CREATOR_AFFILIATE = individual account, earns commission per sale
  DROPSHIPPER = posts multiple unrelated products with generic descriptions

Step 4: Edge Cases

• Non-Shop posts in results: Drop posts where caption has no shop signal AND no product link
• Same product from many creators: De-duplicate by product name; count unique promoters as a "sales momentum" signal
• Saturated niche (> 50 active sellers): Flag as HIGH_COMPETITION; present gap analysis (underserved sub-niches)
• Views inflated by one viral post: Use median views across seller's last 10 posts as the signal, not max

Output Format

# TikTok Shop Seller Map: [NICHE]
Posts scanned: [N] | Unique sellers: [N] | Brands: [N] | Creator-affiliates: [N] | Date: [DATE]

## Top Sellers by Sales Signal
| Seller | Type | Product(s) | Avg Views/Post | Shop Posts | Signal Score |
|--------|------|-----------|----------------|-----------|-------------|
| @[handle] | Creator | [product] | [N] | [N] | [0.XX] |

## Top Products (by Promotion Frequency)
| Product Name | # Sellers Promoting | Avg Post Views | Price Range |
|-------------|--------------------|--------------------|-------------|
| [product] | [N] | [N] | $[X]-$[X] |

## Market Saturation
Competition level: [LOW / MEDIUM / HIGH] ([N] active sellers)
Potential gap: [sub-niche or product type with < 3 sellers]

Troubleshooting

Hashtag returns non-shop content: Combine niche hashtag with #tiktokshop in the same search to anchor on shop-linked posts. Can't determine product price: TikTok Shop prices aren't always in the video — note URL pattern includes product ID which can be cross-referenced manually. All results from one mega-creator: Add max_posts_per_creator = 5 to surface diverse sellers.